graph LR A["Download daily Arxiv articles"] --> B["Predict and Filter LLM topic"] B --> C["Summarize short docs"] B --> D["Summarize by Map-Reduce long docs"] C --> E["Update website with summaries daily"] D --> E
Welcome to the Bayesian beagle blog! This project is a unique intersection of machine learning and scientific communication, providing a platform where readers can quickly get insights from the latest research papers hosted on ArXiv. Utilizing state-of-the-art Large Language Models (LLMs), our system generates concise, comprehensible summaries of complex research articles, covering a wide array of disciplines.
Our blog is built using Quarto, an open-source scientific and technical publishing system designed for creating beautiful, data-driven content. It is then published with Netlify.